EECS 401: Probabilistic Methods in Engineering.

University of Michigan, Winter 2010

Section 1
MW 9-10:30 (EECS 1303), F 9:30-10:30 (EECS 1303)
Instructor: Clayton Scott
Office: 4433 EECS
Office hours: M/F 1-2:30
Section 2
MW 9-10:30 (EECS 3427), F 9:30-10:30 (EECS 3427)
Instructor: Sandeep Pradhan
Office: 4240 EECS
Office hours: M/Th 2:30-4

Required text: Introduction to Probability, Bertsekas and Tsitsiklis, 1st or 2nd edition. Note that this book has a website. On that website are solutions to all of the book's exercises, as well as additional excercises without solutions.

Books on reserve at the library

Axioms of probability, counting, conditional probability, independence, Bayes rule, discrete and continuous random variables, expectation, joint distributions, statistical inference, random processes (Chapters 1-4 and parts of the remaining chapters). We will also cover applications in EECS including communication, signal processing, and reliability theory.


Homeworks: 25%
Exam 1: 25% (Tues. Feb. 9, 6-8 PM, Dow 1013)
Exam 2: 25% (Tues. March 16, 6-8 PM, GGBrown 1504)
Exam 3: 25% (Tues., April 27, 1:30 PM - 3:30 PM, location TBA)

The final grade will be set on a curve, with the median grade (among undergraduates) as a B. Graduate students will be graded on a different curve.

All exams will be closed book/notes and last for 2 hours. Each exam will mostly cover material since the previous exam, but understanding of earlier material will still be expected. Both sections will take the same exams at the same time.

Homeworks will be assigned once per week (except for exam weeks) and due on Tuesdays at 5pm. Your lowest homework score will be dropped. All homeworks will carry equal weight. Both sections will be assigned the same homeworks. Late homeworks will not be accepted except in special cases such as a serious illness.

All homework assignments are to be completed on your own. You are allowed to consult with other students during the conceptualization of a solution, but all written work, whether in scrap or final form, is to be generated by you working alone. You are also not allowed to use, or in any way derive advantage from, solutions prepared by other students, or in prior years.

Honor Code:
All undergraduate and graduate students are expected to abide by the College of Engineering Honor Code as stated in the Student Handbook and the Honor Code Pamphlet.

Students with Disabilities:
Any student with a documented disability needing academic adjustments or accommodations is requested to speak with their instructor during the first two weeks of class. All discussions will remain confidential.


The study of probability, statistics, and random processes can be fun and rewarding, but it may also require patience and perseverance. You will need to develop new critical thinking skills. Unlike some undergraduate engineering courses, you will not get through the course by simply memorizing a few key formulas. There is some structure to the different problem solving methods, and we will do our best to explain that structure, but many problems will not fit into a nice clean mold. Because of this, we offer the following advice: